Identification of Chrysanthemum Flower Based on Color and Flower Form using Sobel Edge and Artificial Neural Network
Arie Qur’ania1, Prihastuti Harsani2, Veni Kertayu Putri3
1Arie Qur’ania, Department of Computer Science, Pakuan University, Indonesia.
2Prihastuti Harsani, Department of Computer Science, Pakuan University, Indonesia.
3Veni Kertayu Putri, Department of Computer Science, Pakuan University, Indonesia.
Manuscript received on 02 August 2019 | Revised Manuscript received on 25 August 2019 | Manuscript Published on 05 September 2019 | PP: 71-75 | Volume-8 Issue-2S7 July 2019 | Retrieval Number: B10140782S719/2019©BEIESP | DOI: 10.35940/ijrte.B1014.0782S719
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Chrysanthemum is a popular ornamental plant in Indonesia because it has a variety of shapes and colors that attract a lot of attention. In addition to the trimmer, this flower can be used as a mosquito repellent and also absorbs dirty air pollution. Chrysanthemum flowers can be distinguished by color and shape with two types of ways to grow Chrysanthemum flowers that grow in clusters are called spray and also flowers that grow with no cluster or a flower per stalk. In addition, Chrysanthemum flowers have various color variations including pink, purple, yellow, white, orange, and red. The purpose of this study is to identify the type of Chrysanthemum flowers using extraction of Red, Green, Blue (RGB) color features and characteristic extraction using a Sobel edge detection, for his identification method using Artificial Neural Networks. Chrysanthemum data are white puma, Vania, Iranian, purple aster, and pink standard used in this research consisted of 100 training data and 50 tests data. The test was done with four tests that is identification with form extraction (Sobel) yielded accuracy value equal to 59.52%, identification with color and shape extraction yield accuracy value equal to 65.36%, identification with color extraction on flower and base flower plate yield value accuracy of 69.44%, and identification with color extraction yields an accuracy value of 75.35%.
Keywords: Identify Chrysanthemum, Sobel, Artificial Neural Network.
Scope of the Article: Artificial Life and Societies